VP, Data Platform – Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of and enhance a collection of internal data products offered as verified capabilities and agreements.

• Oversee the engineering process that transforms food records from raw data to scored, published outputs.

• Establish and execute a deployment strategy that eliminates the single-gatekeeper bottleneck.

• Define gold-certification through code by utilizing documented quality criteria.

• Develop and manage the data platform as a suite of products with well-defined contracts for domain teams.

• Ensure data security and governance, enforce least privilege, transition key data products to general availability, and phase out ad-hoc database credentials.

• Implement observability measures for platform health.

• Apply medallion architecture and differentiate pipeline state from food facts.

• Facilitate secure access via MCPs and other AI-friendly interfaces.

• Foster operational excellence and reusable entity-resolution services.

• Execute automated, agentic workflows with development harnesses.

• Supervise individual contributors in data engineering.

• Establish AI-native engineering standards and architectural guidelines for probabilistic systems.

⛳️ Requirements

• A minimum of 10 years of experience in data engineering, data platforms, or infrastructure, including leadership of teams.

• Proven history of creating data products and teams from inception to execution.

• In-depth expertise in data contracts, medallion or similar quality architectures, and promotion discipline.

• Strong judgment in data security, including principles of least privilege, trust boundaries, and access control.

• Proficiency in AI-assisted and agentic engineering as a primary operational approach.

• Strong SQL skills and systems thinking that spans UI, API, database, and infrastructure boundaries.

• Capability to thrive in an ambiguous, fast-paced startup environment.

• Experience with MCPs, capability layers, or API-first data access methodologies.

• Familiarity with observability tools and production diagnostics.

• Experience working with Postgres, DuckDB or MotherDuck, and cloud infrastructure.

• Background in developing internal developer tools or data-product platforms.

🏝️ Benefits

• Competitive compensation.

• Meaningful equity.

• Rapid impact.

• Collaborate directly with the CDO on the architecture and operation safeguarding the company's core asset.